Kimi K2 0711 vs Saba
Updated October 21, 2026. 4 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Neither model has a coding score yet, so the two cannot be ranked on coding.
Kimi K2 0711 has the edge where the context window is larger, 131K against 33K tokens.
- Shared results
- 4
- Kimi K2 0711 only
- 32
- Saba only
- 0
- Like-for-like categories
- 3 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Kimi K2 0711
Kimi K2 0711 leads, 12.7 against 6.5.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Kimi K2 0711 has a GPQA Diamond result, 71.5%.
Directional only
Math
AIME
No call
Only Kimi K2 0711 has a AIME result, 62.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Kimi K2 0711 has a MMLU Pro result, 79.4%.
Directional only
Web design
Design Arena: websites
No call
Only Kimi K2 0711 has a Design Arena: websites result, 1050.
Directional only
Long documents
Listed context window
Kimi K2 0711
Kimi K2 0711 takes 131K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Saba
Kimi K2 0711 $0.0017, Saba $0.0005 per turn.
List prices
At a glance
- Coding index
- Kimi K2 0711 not benchmarked, Saba not benchmarked.
- Widest category
- Knowledge, 21.3 points apart on average over 1 shared benchmark.
- Widest single gap
- GPQA Diamond (Artificial Analysis run): Kimi K2 0711 76.6% against Saba 42.4%, 34.2 points apart on a 0 to 100 scale.
- Output price
- Kimi K2 0711 $2.30 against Saba $0.60 per million output tokens, 3.8x apart.
- Context window
- Kimi K2 0711 takes 131K tokens, Saba 33K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Kimi K2 0711 | Bars | Saba | Ties |
|---|---|---|---|---|
| Intelligence | 1 | 0 | ||
| Reasoning | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| All shared boards | 4 | 0 |
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| Aider polyglot | 59.1% | Not measured | Only Kimi K2 0711 measured |
| SWE-bench Verified | 71.2% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Vals AI) | 70.5% | Not measured | Only Kimi K2 0711 measured |
| LiveCodeBench (Artificial Analysis run) | 55.6% | Not measured | Only Kimi K2 0711 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 15.9% | Not measured | Only Kimi K2 0711 measured |
| Terminal-Bench | 27.8% | Not measured | Only Kimi K2 0711 measured |
| GSO-Bench | 4.9% | Not measured | Only Kimi K2 0711 measured |
| WeirdML | 39.4% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.7 | 6.5 | Kimi K2 0711 |
| Epoch Capabilities Index | 140.0 | Not measured | Only Kimi K2 0711 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| GPQA Diamond | 71.5% | Not measured | Only Kimi K2 0711 measured |
| GPQA Diamond (Artificial Analysis run) | 76.6% | 42.4% | Kimi K2 0711 |
| Humanity's Last Exam (Artificial Analysis run) | 7.4% | 4.3% | Kimi K2 0711 |
| SimpleBench | 26.3% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| AIME | 62.7% | Not measured | Only Kimi K2 0711 measured |
| MATH 500 (Vals AI) | 94.2% | Not measured | Only Kimi K2 0711 measured |
| MGSM (Vals AI) | 91.0% | Not measured | Only Kimi K2 0711 measured |
| AA Math Index | 57.0 | Not measured | Only Kimi K2 0711 measured |
| AIME 2025 (Artificial Analysis run) | 57.0% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| MMLU Pro | 79.4% | Not measured | Only Kimi K2 0711 measured |
| LegalBench (Vals AI) | 81.5% | Not measured | Only Kimi K2 0711 measured |
| CorpFin (Vals AI) | 50.4% | Not measured | Only Kimi K2 0711 measured |
| TaxEval (Vals AI) | 70.2% | Not measured | Only Kimi K2 0711 measured |
| MedQA (Vals AI) | 84.0% | Not measured | Only Kimi K2 0711 measured |
| MMLU Pro (Artificial Analysis run) | 82.4% | 61.1% | Kimi K2 0711 |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| Design Arena: websites | 1050 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: UI components | 1030 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: game dev | 974 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: data viz | 1018 | Not measured | Only Kimi K2 0711 measured |
| Design Arena: all code categories | 1033 | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 4 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| IFBench | 41.5% | Not measured | Only Kimi K2 0711 measured |
| Long context reasoning (AA-LCR) | 53.0% | Not measured | Only Kimi K2 0711 measured |
| Fiction.LiveBench | 61.1% | Not measured | Only Kimi K2 0711 measured |
| Creative writing (Lech Mazur) | 85.6% | Not measured | Only Kimi K2 0711 measured |
| CL-bench | 11.9% | Not measured | Only Kimi K2 0711 measured |
| Neither model has a result on the other 41 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Kimi K2 0711 | Saba | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Saba costs less
Repository review
50K input + 3K output tokens
Saba costs less
Agent loop
200K input + 10K output tokens
Saba costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | MoonshotAI Kimi K2 0711 | Mistral Saba |
|---|---|---|
| Maker | Moonshot AI | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | July 11, 2025 | February 17, 2025 |
| Context window | 131K | 33K |
| Input $/Mtok | $0.57 | $0.20 |
| Output $/Mtok | $2.30 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Kimi K2 0711 better than Saba for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Kimi K2 0711 has the edge where the context window is larger, 131K against 33K tokens.
Which is cheaper, Kimi K2 0711 or Saba?
Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; Saba costs $0.20 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Kimi K2 0711 or Saba?
Kimi K2 0711, with 131K tokens against 33K.
How many benchmarks is the Kimi K2 0711 vs Saba comparison based on?
4 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and Saba's on 0. Where only one model has a result, the page says so instead of naming a winner.